ARL6IP5 Antibody

What is ARL6IP5 and what experimental approaches can be used to study its function?

ARL6IP5 (ADP-ribosylation-like factor 6 interacting protein 5) is a multifunctional protein also known as JWA in humans, Addicsin in mice, and GTRAP 3-18 or JM4 in rats. It belongs to the PRAF3 family with a large prenylated acceptor domain 1, primarily involved in intracellular protein trafficking .

To study ARL6IP5 function, researchers typically employ:

• Genetic manipulation: Overexpression (OE) and knockdown (KD) studies using plasmid transfection. For example, transfection with 1 μg ARL6IP5 plasmid mixed with 50 μL serum-free media and 3 µL Lipofectamine 2000, followed by 48-hour incubation .

• Protein interaction assays: Co-immunoprecipitation to identify binding partners (e.g., ATG12 interaction) .

• Subcellular localization: Immunofluorescence microscopy using anti-ARL6IP5 antibodies (typically at 0.25-2 μg/mL concentration) .

• Functional assays: Measurement of autophagy (LC3BII levels), apoptosis (TUNEL assay), and cellular proliferation in response to ARL6IP5 modulation .

What is the recommended protocol for optimizing Western blot analysis using ARL6IP5 antibodies?

For optimal Western blot results with ARL6IP5 antibodies:

• Sample preparation: Extract proteins using RIPA buffer with protease inhibitors

• Protein loading: 20-30 μg total protein per lane

• Antibody concentration:

  • Primary antibody: 0.04-0.4 μg/mL for commercially available antibodies

  • Secondary antibody: 1:5000-1:10000 dilution of HRP-conjugated antibody

Optimization tips:

• ARL6IP5 has a calculated molecular weight of 22kDa , so use appropriate percentage gels (12-15%)

• Some antibodies detect multiple bands (22kDa and 48kDa) , so validation with positive controls is essential

• For difficult samples, try HBAM buffer systems which have shown better results than enhanced buffers

• Transfer time: 60-90 minutes at 100V for efficient protein transfer

What are the key considerations for selecting an appropriate anti-ARL6IP5 antibody for immunohistochemistry?

When selecting an anti-ARL6IP5 antibody for immunohistochemistry (IHC):

• Epitope specificity: Choose antibodies targeting well-conserved regions. The C-terminal region (sequence: NRLTDYISKVKE) has proven effective for generating specific antibodies .

• Validation status: Select antibodies with documented IHC validation. For example, Atlas Antibodies' HPA015540 has been validated through the Human Protein Atlas project .

• Species reactivity: Ensure compatibility with your experimental model. Available antibodies show reactivity to:

  • Human only

  • Human and mouse

  • Multiple species

• Staining protocol optimization:

  • Recommended dilution: 1:50-1:200 for most commercial antibodies

  • Antigen retrieval: Cell conditioning solution (CC1) has shown good results

  • Detection system: DAB-based visualization works effectively with ARL6IP5 antibodies

• Semi-quantitative scoring method for ARL6IP5 expression:

  Score	Intensity
  0	Negative
  1	Weak
  2	Moderate
  3	Strong

This scoring system has been successfully employed in clinical studies correlating ARL6IP5 expression with patient outcomes .

How can I design experiments to investigate ARL6IP5's role in autophagy and its relationship to neurodegenerative diseases?

To investigate ARL6IP5's role in autophagy and neurodegenerative diseases, consider this comprehensive experimental approach:

Cell-based models:

• Establish relevant cellular models:

  • SH-SY5Y cells with stable expression of wild-type or mutant (A53T) α-synuclein

  • Primary neurons from PD model mice

• Manipulate ARL6IP5 expression:

  • Overexpression: Transfect with ARL6IP5 plasmid

  • Knockdown: Use siRNA targeting ARL6IP5 (verified to reduce expression to 16±3% of control levels)

• Autophagy assessment:

  • Western blot for LC3B-II (autophagy marker)

  • GFP-LC3B puncta quantification (normal cells show 8±2 puncta/cell; increased to 32±6 with enhanced autophagy)

  • Co-localization of ARL6IP5 with ATG12 and other autophagy proteins

  • Autophagy flux assays with bafilomycin A1

• α-synuclein aggregate measurement:

  • A11 antibody reactivity to measure toxic aggregates

  • GFP fluorescence quantification in A53T α-synuclein-GFP expressing cells

  • Measurement of LDH release to assess cellular toxicity

Mechanistic investigations:

• Evaluate the ARL6IP5/Rab1/ATG12 axis through co-immunoprecipitation

• Assess subcellular localization changes of ARL6IP5 during autophagy induction

• Determine the effects of autophagy inhibitors on ARL6IP5-mediated neuroprotection

Research has shown that ARL6IP5 overexpression increases autophagy by 150±54% compared to control, and reduces A53T α-synuclein fluorescence from 58±24 in control cells to 28±33 in ARL6IP5-transfected cells (p<0.0001) .

What experimental approaches should be used to investigate ARL6IP5's role in cisplatin resistance and DNA repair mechanisms?

To investigate ARL6IP5's role in cisplatin resistance and DNA repair:

Cell culture experiments:

• Establish cisplatin-resistant (CisR) cell lines:

  • Expose cancer cells (e.g., ovarian cancer lines OV90, SKOV3) to increasing concentrations of cisplatin

  • Validate resistance through IC50 determination

• Manipulate ARL6IP5 expression:

  • Overexpression: Transfect with ARL6IP5 plasmid

  • Knockdown: Use siRNA targeting ARL6IP5

  • Treatment with recombinant ARL6IP5 protein (rARL6IP5)

• Cell viability and apoptosis assays:

  • MTT/CCK-8 assays to determine cisplatin sensitivity

  • TUNEL assays to quantify apoptosis

  • Annexin V/PI staining followed by flow cytometry

DNA repair assessment:

• Evaluate DNA repair proteins expression:

  • Western blot for XRCC1, PARP1, and other DNA repair proteins

  • Immunofluorescence for repair foci formation following cisplatin treatment

  • Comet assay to measure DNA damage and repair kinetics

• Functional repair assays:

  • Host cell reactivation assays

  • Homologous recombination reporter assays

  • Non-homologous end joining assays

Combination treatments:

• Compare efficacy of cisplatin, olaparib, and rARL6IP5 alone and in combination:

Research has demonstrated that rARL6IP5 had greater apoptotic efficacy than cisplatin or olaparib in both cisplatin-sensitive and cisplatin-resistant ovarian cancer cells. Notably, while cisplatin and olaparib lost efficacy in resistant cells, rARL6IP5 maintained its apoptotic effect, suggesting it acts through pathways that remain functional despite cisplatin resistance .

How can contradictory findings about ARL6IP5 function in different cell types be experimentally addressed?

To address contradictory findings about ARL6IP5 function across different cell types:

Comprehensive cell line characterization:

• Conduct systematic analysis across multiple cell types:

  • Neuronal cells (SH-SY5Y, primary neurons)

  • Cancer cells (OV90, SKOV3, etc.)

  • Normal cells (fibroblasts, HEK293)

• Baseline expression profiling:

  • Quantitative RT-PCR for ARL6IP5 mRNA levels

  • Western blot for protein expression using multiple validated antibodies

  • Single-cell RNA-seq to identify cell populations with varying expression

Interactome analysis:

• Identify cell-type specific binding partners:

  • Co-immunoprecipitation followed by mass spectrometry

  • Proximity labeling (BioID, APEX) to capture transient interactions

  • Yeast two-hybrid screening with cell-type specific cDNA libraries

• Post-translational modification analysis:

  • Phosphorylation: Phospho-specific antibodies or phosphoproteomic analysis

  • Ubiquitination: Immunoprecipitation under denaturing conditions

  • Other modifications: Mass spectrometry-based approaches

Functional rescue experiments:

• Generate ARL6IP5 knockout in diverse cell lines using CRISPR-Cas9

• Perform complementation with:

  • Wild-type ARL6IP5

  • Domain-specific mutants

  • Chimeric proteins with interacting partners

Context-dependent function assessment:

• Autophagy context: Compare autophagy induction by ARL6IP5 in:

  • Neurons (where it increases autophagy by 150±54%)

  • Cancer cells (where its role may differ)

• DNA repair context: Evaluate XRCC1/PARP1 interaction with ARL6IP5 in:

  • Cisplatin-sensitive vs. resistant cancer cells

  • Normal vs. cancer cells

What are the optimal experimental conditions for studying the therapeutic potential of recombinant ARL6IP5 protein?

To study the therapeutic potential of recombinant ARL6IP5 protein (rARL6IP5):

Protein production and quality control:

• Expression system selection:

  • Bacterial (E. coli): Suitable for non-glycosylated versions

  • Mammalian (CHO cells): For properly folded protein with post-translational modifications

  • Insect cells (Sf9): Alternative for complex proteins

• Purification strategy:

  • Affinity chromatography (His-tag or GST-tag)

  • Size exclusion chromatography for high purity

  • Endotoxin removal for in vivo applications

• Quality assessment:

  • SDS-PAGE and Western blot

  • Circular dichroism for secondary structure

  • Activity assays to confirm functionality

Cellular uptake and biodistribution:

• Labeling strategies:

  • Fluorescent tagging (maintaining function)

  • Radioisotope labeling for in vivo tracking

• Uptake mechanisms:

  • Flow cytometry to quantify cellular uptake

  • Confocal microscopy for intracellular localization

  • Endocytosis inhibitors to determine entry pathways

Functional assays:

• Cancer models:

  • Apoptosis induction: TUNEL assay with standard conditions (72h incubation at 37°C, 5% CO2)

  • Concentration optimization: Test range from 0.5-5 μg/mL

  • Combination treatments with conventional therapies

• Neurodegenerative models:

  • α-synuclein aggregation: Fluorescence measurement in GFP-A53T expressing cells

  • Autophagy induction: LC3B-II Western blot and puncta quantification

  • Neuroprotection assays: LDH release and cell viability measurements

In vivo efficacy studies:

• Dose optimization:

  • Range-finding studies (based on in vitro EC50)

  • Administration route comparison (IV, IP, etc.)

  • Pharmacokinetic profiling

• Disease models:

  • Xenograft models for cancer studies

  • α-synuclein transgenic mice for PD studies

  • Toxicity studies in multiple species

Research has shown that rARL6IP5 has significant therapeutic potential in cisplatin-resistant ovarian cancer, with greater apoptotic efficacy than conventional chemotherapeutics .

What methodological approaches can be used to elucidate the molecular mechanisms by which ARL6IP5 regulates both autophagy and DNA repair pathways?

To elucidate how ARL6IP5 simultaneously regulates autophagy and DNA repair:

Structural biology approaches:

• Domain mapping:

  • Generate truncation mutants to identify functional domains

  • Assess interaction with ATG12 (autophagy) vs. XRCC1/PARP1 (DNA repair)

  • Determine if interactions are mutually exclusive or can occur simultaneously

• Structural determination:

  • X-ray crystallography of ARL6IP5 alone and in complexes

  • Cryo-EM for larger protein assemblies

  • NMR for dynamic interaction studies

Temporal regulation analysis:

• Real-time imaging:

  • Live-cell imaging with fluorescently tagged ARL6IP5 and partners

  • FRET/BRET assays to measure protein-protein interactions in real-time

  • Photoactivation studies to track protein movement between compartments

• Stress-induced relocalization:

  • Track ARL6IP5 localization after:

    • DNA damage (cisplatin treatment)

    • Autophagy induction (starvation, rapamycin)

    • Combined stressors

  • Quantify colocalization with organelle markers

Signaling pathway integration:

• Phosphoproteomics:

  • Global phosphorylation changes upon ARL6IP5 modulation

  • Identification of kinases/phosphatases regulating ARL6IP5

  • Mutational analysis of key phosphorylation sites

• Transcriptional regulation:

  • RNA-seq after ARL6IP5 modulation

  • ChIP-seq to identify transcription factors regulated by ARL6IP5

  • Pathway enrichment analysis to identify coordinated gene programs

Disease context-specific mechanisms:

• Neurodegenerative disease models:

  • Compare ARL6IP5 function in:

    • α-synuclein models (PD)

    • Amyloid-β models (AD)

    • SOD1 models (ALS)

  • Assess if autophagy predominates in these contexts

• Cancer models:

  • Compare mechanism in cisplatin-sensitive vs. resistant cells

  • Determine if DNA repair functions predominate in cancer contexts

  • Assess if tumor microenvironment influences ARL6IP5 function

Experimental evidence indicates ARL6IP5 serves as a multifunctional protein capable of:

• Binding ATG12 to promote autophagy and reduce α-synuclein aggregation

• Suppressing DNA repair proteins XRCC1 and PARP1 to enhance cisplatin sensitivity

Understanding the molecular switch determining pathway selection would provide critical insights for therapeutic targeting.

What troubleshooting approaches are recommended for inconsistent staining patterns with ARL6IP5 antibodies in immunohistochemistry?

When encountering inconsistent staining patterns with ARL6IP5 antibodies:

Antibody validation:

• Cross-validation with multiple antibodies:

  • Compare polyclonal antibodies from different sources

  • Verify with antibodies targeting different epitopes

  • Include knockout/knockdown controls

• Epitope masking assessment:

  • Test multiple antigen retrieval methods:

    • Heat-induced (citrate buffer, pH 6.0)

    • Enzymatic (proteinase K)

    • High pH (EDTA buffer, pH 9.0)

  • Extend retrieval times for formalin-fixed tissues

Sample preparation optimization:

• Fixation considerations:

  • Optimize fixation time (overfixation can mask epitopes)

  • Compare different fixatives (formalin vs. alcohol-based)

  • Prepare fresh frozen sections as alternative

• Tissue processing:

  • Control section thickness (4μm optimal for most applications)

  • Use positive control tissues (thymus has shown consistent expression)

  • Process experimental and control tissues simultaneously

Detection system troubleshooting:

• Signal amplification:

  • Try polymer-based detection systems

  • Consider tyramide signal amplification for weak signals

  • Optimize incubation times and temperatures

• Background reduction:

  • Include blocking steps (serum from secondary antibody species)

  • Add detergents (0.1-0.3% Triton X-100) to reduce non-specific binding

  • Use avidin/biotin blocking for tissues with endogenous biotin

Scoring system standardization:
Implement the validated semi-quantitative scoring method :

• Have multiple observers score independently

• Resolve discrepancies through consensus review

• Include training sets for new observers to ensure consistency

How can researchers design experiments to determine whether ARL6IP5's effects on α-synuclein are direct or indirect?

To determine if ARL6IP5 directly or indirectly affects α-synuclein:

Direct interaction studies:

• In vitro binding assays:

  • Pull-down assays with purified proteins

  • Surface plasmon resonance to measure binding kinetics

  • Isothermal titration calorimetry for thermodynamic parameters

• Cellular colocalization:

  • Super-resolution microscopy (STED, STORM)

  • Proximity ligation assay to detect close association (<40nm)

  • FRET analysis between tagged proteins

Autophagy-mediated clearance assessment:

• Autophagy manipulation:

  • Use autophagy inhibitors (3-MA, bafilomycin A1) alongside ARL6IP5 overexpression

  • Compare wild-type ATG5/7 with autophagy-deficient cells

  • Quantify α-synuclein levels with immunoblotting and fluorescence

• Selective autophagy markers:

  • Assess p62/SQSTM1 colocalization with α-synuclein

  • Evaluate ubiquitination status of α-synuclein

  • Determine if ARL6IP5 affects α-synuclein ubiquitination

Mechanistic dissection:

• Domain mapping:

  • Generate ARL6IP5 mutants lacking autophagy-inducing domains

  • Test if these mutants still affect α-synuclein levels

  • Map minimal region required for effect

• Interactome comparison:

  • Identify proteins that interact with both ARL6IP5 and α-synuclein

  • Silence these mediators to determine if they're required for the effect

  • Reconstitute the pathway with purified components

Experimental evidence suggests that ARL6IP5 reduces α-synuclein burden by enhancing autophagy rather than direct interaction:

• ARL6IP5 overexpression decreases A53T α-synuclein fluorescence by approximately 52% (from 58±24 to 28±33, p<0.0001)

• ARL6IP5 knockdown increases α-synuclein toxicity by 15±7% (p=0.018)

• ARL6IP5 increases autophagy marker LC3B-II by approximately 155±46% when co-expressed with α-synuclein

How can multi-omics approaches be integrated to understand the tissue-specific functions of ARL6IP5?

To integrate multi-omics for understanding tissue-specific ARL6IP5 functions:

Comprehensive multi-omics data collection:

• Transcriptomics:

  • RNA-seq across tissues with differential ARL6IP5 expression

  • Single-cell RNA-seq to identify cell-type specific expression patterns

  • Alternative splicing analysis to detect tissue-specific isoforms

• Proteomics:

  • Global proteome profiling after ARL6IP5 modulation

  • Interactome analysis in different tissues/cell types

  • Post-translational modification mapping

• Metabolomics:

  • Untargeted metabolomics to identify affected pathways

  • Stable isotope tracing to track metabolic flux

  • Lipid profiling given ARL6IP5's membrane association

Integrative computational analysis:

• Network-based integration:

  • Construct protein-protein interaction networks

  • Pathway enrichment analysis across omics layers

  • Identify tissue-specific network modules

• Machine learning approaches:

  • Predictive modeling of ARL6IP5 functions based on multi-omics signatures

  • Feature importance analysis to identify key regulatory nodes

  • Clustering to identify functionally similar tissues

Functional validation of predictions:

• Tissue-specific knockouts:

  • Generate conditional knockout models targeting specific tissues

  • Compare phenotypes across neural, cancer, and normal tissues

  • Conduct rescue experiments with tissue-specific promoters

• 3D organoid models:

  • Develop organoids from different tissues with ARL6IP5 modulation

  • Compare response to stressors (e.g., cisplatin, nutrient deprivation)

  • Assess tissue-specific pathways through targeted interventions

Clinical correlation:

• Human sample analysis:

  • Correlate ARL6IP5 expression with clinical outcomes across tissues

  • Apply the validated semi-quantitative scoring system (0-3)

  • Integrate with patient genomic and transcriptomic data

• Biomarker development:

  • Identify tissue-specific signatures associated with ARL6IP5 function

  • Develop predictive models for treatment response

  • Stratify patients based on multi-omics profiles

What are the latest methodological approaches for studying ARL6IP5 in the context of neuroinflammation?

For studying ARL6IP5 in neuroinflammation contexts:

Advanced cellular models:

• Microglia-neuron co-culture systems:

  • Primary cultures or iPSC-derived cells

  • 3D spheroid co-cultures to model tissue architecture

  • Microfluidic platforms for controlled cell-cell interaction

• Brain organoids:

  • Develop region-specific organoids (midbrain for PD studies)

  • Generate organoids with multiple cell types (neurons, astrocytes, microglia)

  • Gene editing to modulate ARL6IP5 expression in specific cell types

Inflammation assessment:

• Cytokine profiling:

  • Multiplex cytokine arrays after ARL6IP5 modulation

  • Single-cell secretome analysis

  • In situ cytokine detection in tissue sections

• Glial activation markers:

  • Flow cytometry for microglial/astrocyte activation markers

  • Live imaging of calcium signaling and morphological changes

  • Transcriptional profiling of inflammatory gene signatures

Spatial transcriptomics and proteomics:

• Spatial mapping techniques:

  • Visium spatial transcriptomics to map expression patterns

  • CODEX multiplexed protein imaging

  • MERFISH for single-cell spatial transcriptomics

• Single-cell multi-omics:

  • CITE-seq for simultaneous protein and RNA profiling

  • Single-cell ATAC-seq to assess chromatin accessibility

  • Spatial proteomics with subcellular resolution

In vivo neuroinflammation models:

• Disease-specific models:

  • α-synuclein preformed fibril (PFF) injection models

  • LPS-induced neuroinflammation

  • Transgenic models with cell-type specific ARL6IP5 modulation

• Advanced imaging:

  • Two-photon imaging of glial dynamics in live animals

  • PET imaging with TSPO ligands for neuroinflammation

  • Multimodal imaging combining structural and functional readouts

Mechanistic studies:

• Investigate if ARL6IP5's autophagy-promoting function (150±54% increase) affects:

  • Inflammasome activation and regulation

  • Clearance of protein aggregates triggering inflammation

  • Mitophagy of damaged mitochondria releasing DAMPs

• Explore potential direct interactions with:

  • NF-κB pathway components

  • NLRP3 inflammasome proteins

  • Toll-like receptors and downstream mediators

What experimental design would best assess the potential of ARL6IP5 as a prognostic biomarker across different cancer types?

To assess ARL6IP5 as a cancer prognostic biomarker:

Statistical analysis and biomarker validation:

• Prognostic value assessment:

  • Kaplan-Meier survival analysis stratified by ARL6IP5 expression

  • Cox proportional hazards regression for multivariate analysis

  • Time-dependent ROC curve analysis for predictive accuracy

• Cross-validation approaches:

  • Training/validation cohort design (70/30 split)

  • Leave-one-out cross-validation

  • External validation in independent cohorts

Molecular correlation studies:

• Multi-platform analysis:

  • Correlate protein expression with mRNA levels

  • Assess genomic alterations affecting ARL6IP5 (copy number, mutations)

  • Integrate with pathway activation signatures

• Functional subtype identification:

  • Determine if ARL6IP5 has different prognostic value in:

    • Different molecular subtypes of each cancer

    • Patients with specific treatment histories

    • Tumors with varied DNA repair capacities

Liquid biopsy development:

• Circulating biomarker assessment:

  • Evaluate ARL6IP5 in circulating tumor cells

  • Assess ARL6IP5 in extracellular vesicles

  • Develop sensitive detection methods (e.g., digital ELISA)

• Longitudinal monitoring:

  • Serial sampling during treatment and follow-up

  • Correlation with disease progression and treatment response

  • Integration with other established biomarkers

How can contradictory findings about ARL6IP5 function in different experimental models be reconciled for translational development?

To reconcile contradictory findings about ARL6IP5 for translational development:

Systematic review and meta-analysis:

• Structured comparison across studies:

  • Catalog experimental conditions (cell types, assays, endpoints)

  • Standardize effect sizes for cross-study comparison

  • Identify patterns related to specific experimental variables

• Quality assessment framework:

  • Evaluate methodological rigor of contradictory studies

  • Assess antibody validation standards

  • Examine statistical approaches and sample sizes

Context-dependent regulation mapping:

• Cellular context classification:

  • Normal vs. cancer cells

  • Neuronal vs. non-neuronal cells

  • Proliferating vs. differentiated cells

• Stress context analysis:

  • Baseline vs. genotoxic stress (cisplatin)

  • Proteotoxic stress (protein aggregation)

  • Metabolic stress (nutrient deprivation)

Mechanistic reconciliation experiments:

• Side-by-side comparison in standardized systems:

  • Test multiple functions simultaneously in the same cell type

  • Evaluate concentration-dependent effects

  • Assess temporal dynamics of different functions

• Isoform-specific analysis:

  • Characterize expression of different splice variants across tissues

  • Test functional differences between isoforms

  • Develop isoform-specific detection methods

Translational decision framework:

• Therapeutic context definition:

  • Clearly define disease context (cancer type, neurodegeneration type)

  • Establish primary pathway of interest (autophagy, DNA repair)

  • Identify biomarkers for context-appropriate application

• Risk mitigation strategies:

  • Develop companion diagnostics for appropriate patient selection

  • Design combination approaches addressing potential compensatory mechanisms

  • Establish monitoring protocols for expected and unexpected effects

Reconciling contradictory findings about ARL6IP5 is essential as research shows dual functions:

• Promoting autophagy and reducing α-synuclein aggregation in neurodegenerative contexts

• Suppressing DNA repair and enhancing cisplatin sensitivity in cancer contexts

These differences may represent true biological context-dependency rather than experimental artifacts, suggesting context-specific therapeutic applications.